improve performance_report notebook #1271
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benisraeldan
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noamzbr
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Apr 14, 2022
| This check helps you compare your model's performance between two datasets. | ||
| The default metric that are used are F1, Percision, and Recall for Classification | ||
| and Negative Root Mean Square Error, Negative Mean Absolute Error, and R2 for Regression. RMSE and MAE Scorers are | ||
| negative because we subscribe to the convention of sklearn to evaluate a model. |
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| negative because we subscribe to the convention of sklearn to evaluate a model. | |
| negative because we subscribe to the sklearn convention of defining scoring functions |
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Reference Issues/PRs
Resolves #656